{"id":"https://openalex.org/W4409581272","doi":"https://doi.org/10.1109/tii.2025.3556083","title":"Multitask Hybrid Knowledge Distillation for Unsupervised Anomaly Detection","display_name":"Multitask Hybrid Knowledge Distillation for Unsupervised Anomaly Detection","publication_year":2025,"publication_date":"2025-04-18","ids":{"openalex":"https://openalex.org/W4409581272","doi":"https://doi.org/10.1109/tii.2025.3556083"},"language":"en","primary_location":{"id":"doi:10.1109/tii.2025.3556083","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2025.3556083","pdf_url":null,"source":{"id":"https://openalex.org/S184777250","display_name":"IEEE Transactions on Industrial Informatics","issn_l":"1551-3203","issn":["1551-3203","1941-0050"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Industrial Informatics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102747194","display_name":"Muhao Xu","orcid":"https://orcid.org/0000-0002-7084-6170"},"institutions":[{"id":"https://openalex.org/I34949971","display_name":"University of Jinan","ror":"https://ror.org/02mjz6f26","country_code":"CN","type":"education","lineage":["https://openalex.org/I34949971"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Muhao Xu","raw_affiliation_strings":["Shandong Key Laboratory of Ubiquitous Intelligent Computing, School of Information Science and Engineering, University of Jinan, Jinan, China"],"affiliations":[{"raw_affiliation_string":"Shandong Key Laboratory of Ubiquitous Intelligent Computing, School of Information Science and Engineering, University of Jinan, Jinan, China","institution_ids":["https://openalex.org/I34949971"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059287425","display_name":"Cuiping Zhu","orcid":"https://orcid.org/0000-0002-7947-3657"},"institutions":[{"id":"https://openalex.org/I34949971","display_name":"University of Jinan","ror":"https://ror.org/02mjz6f26","country_code":"CN","type":"education","lineage":["https://openalex.org/I34949971"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cuiping Zhu","raw_affiliation_strings":["Shandong Key Laboratory of Ubiquitous Intelligent Computing, School of Information Science and Engineering, University of Jinan, Jinan, China"],"affiliations":[{"raw_affiliation_string":"Shandong Key Laboratory of Ubiquitous Intelligent Computing, School of Information Science and Engineering, University of Jinan, Jinan, China","institution_ids":["https://openalex.org/I34949971"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101504236","display_name":"Guang Feng","orcid":"https://orcid.org/0009-0002-1696-654X"},"institutions":[{"id":"https://openalex.org/I34949971","display_name":"University of Jinan","ror":"https://ror.org/02mjz6f26","country_code":"CN","type":"education","lineage":["https://openalex.org/I34949971"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guang Feng","raw_affiliation_strings":["Shandong Key Laboratory of Ubiquitous Intelligent Computing, School of Information Science and Engineering, University of Jinan, Jinan, China"],"affiliations":[{"raw_affiliation_string":"Shandong Key Laboratory of Ubiquitous Intelligent Computing, School of Information Science and Engineering, University of Jinan, Jinan, China","institution_ids":["https://openalex.org/I34949971"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111036933","display_name":"Sijie Niu","orcid":null},"institutions":[{"id":"https://openalex.org/I34949971","display_name":"University of Jinan","ror":"https://ror.org/02mjz6f26","country_code":"CN","type":"education","lineage":["https://openalex.org/I34949971"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sijie Niu","raw_affiliation_strings":["Shandong Key Laboratory of Ubiquitous Intelligent Computing, School of Information Science and Engineering, University of Jinan, Jinan, China"],"affiliations":[{"raw_affiliation_string":"Shandong Key Laboratory of Ubiquitous Intelligent Computing, School of Information Science and Engineering, University of Jinan, Jinan, China","institution_ids":["https://openalex.org/I34949971"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5102747194"],"corresponding_institution_ids":["https://openalex.org/I34949971"],"apc_list":null,"apc_paid":null,"fwci":12.1264,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.98165972,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":100},"biblio":{"volume":"21","issue":"7","first_page":"5666","last_page":"5676"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9850999712944031,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.6908549070358276},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6097792387008667},{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.5356945991516113},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5108053684234619},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.49636226892471313},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3950396180152893},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34153252840042114},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.09289231896400452}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.6908549070358276},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6097792387008667},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.5356945991516113},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5108053684234619},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.49636226892471313},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3950396180152893},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34153252840042114},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.09289231896400452},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tii.2025.3556083","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2025.3556083","pdf_url":null,"source":{"id":"https://openalex.org/S184777250","display_name":"IEEE Transactions on Industrial Informatics","issn_l":"1551-3203","issn":["1551-3203","1941-0050"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Industrial Informatics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5793342903","display_name":null,"funder_award_id":"62302191","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8886907078","display_name":null,"funder_award_id":"62471202","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W2122646361","https://openalex.org/W2194775991","https://openalex.org/W2788633781","https://openalex.org/W2914570111","https://openalex.org/W2948982773","https://openalex.org/W2963045681","https://openalex.org/W3034314048","https://openalex.org/W3034648032","https://openalex.org/W3035240825","https://openalex.org/W3108027406","https://openalex.org/W3147184966","https://openalex.org/W3169077988","https://openalex.org/W3169651898","https://openalex.org/W3173538657","https://openalex.org/W3175238080","https://openalex.org/W3175716777","https://openalex.org/W4206551889","https://openalex.org/W4210446097","https://openalex.org/W4212874935","https://openalex.org/W4214694907","https://openalex.org/W4292264335","https://openalex.org/W4312605624","https://openalex.org/W4312721464","https://openalex.org/W4312772600","https://openalex.org/W4319299981","https://openalex.org/W4376626035","https://openalex.org/W4386065890","https://openalex.org/W4386071499","https://openalex.org/W4386075837","https://openalex.org/W4390871926","https://openalex.org/W4393307106","https://openalex.org/W4394625793","https://openalex.org/W4394625802","https://openalex.org/W4411244487"],"related_works":["https://openalex.org/W4285233543","https://openalex.org/W4230838436","https://openalex.org/W3196155444","https://openalex.org/W4321844043","https://openalex.org/W3210156800","https://openalex.org/W4390062853","https://openalex.org/W4297883248","https://openalex.org/W4255830763","https://openalex.org/W1583266947","https://openalex.org/W4286799911"],"abstract_inverted_index":{"Detecting":[0],"both":[1],"logical":[2,118,140,162,183],"and":[3,119,143,221],"structural":[4,120],"anomalies":[5,40],"in":[6,88,156,181],"an":[7,222],"unsupervised":[8],"anomaly":[9,191],"detection":[10,141,192],"task":[11],"is":[12,42,80],"a":[13,43,74,102,134,148,216],"significant":[14],"challenge":[15],"due":[16,67,177],"to":[17,33,68,105,115,160,178,194],"the":[18,22,59,69,84,98,124,139,145,154,167,182,196,204,226],"inherent":[19],"differences":[20,155],"between":[21,62,117,158],"two":[23,37,64],"types":[24,38],"of":[25,29,39,71,77,126,198,219,232],"anomalies.":[26],"The":[27],"use":[28],"two-branch":[30],"knowledge":[31],"distillation":[32,136,150],"deal":[34],"with":[35,215],"these":[36,63,94],"separately":[41],"generalized":[44],"approach.":[45,151,200],"However,":[46],"existing":[47],"methods":[48],"often":[49,81,171],"design":[50],"dual":[51],"branches":[52],"separately,":[53],"which":[54],"does":[55],"not":[56],"effectively":[57,165],"utilize":[58],"shared":[60],"information":[61,79],"branches.":[65],"Also,":[66],"introduction":[70],"bottleneck":[72],"layers,":[73],"large":[75],"amount":[76],"detailed":[78],"lost":[82],"during":[83],"reconstruction":[85,175],"process,":[86],"resulting":[87],"many":[89],"false":[90,168],"positives.":[91],"To":[92],"overcome":[93],"drawbacks,":[95],"we":[96,132,164],"structure":[97],"student":[99],"network":[100],"as":[101],"multitask":[103],"model":[104,146],"enhance":[106],"its":[107,113],"feature":[108,179],"extraction":[109],"capability,":[110],"thereby":[111],"improving":[112],"ability":[114],"distinguish":[116],"anomalies,":[121,163],"especially":[122],"under":[123,225],"constraint":[125],"limited":[127],"training":[128],"data.":[129],"In":[130,201],"addition,":[131],"incorporated":[133],"self-supervised":[135],"loss":[137],"within":[138],"branch":[142],"trained":[144],"using":[147],"hybrid":[149],"By":[152],"leveraging":[153],"features":[157],"self-distillations":[159],"detect":[161],"minimized":[166],"positives":[169],"that":[170],"arise":[172],"from":[173],"image":[174],"blurring":[176],"compression":[180],"branch.":[184],"We":[185],"conducted":[186],"experiments":[187],"on":[188,203],"three":[189],"well-known":[190],"datasets":[193],"demonstrate":[195],"effectiveness":[197],"our":[199,210],"particular,":[202],"challenging":[205],"MVTec":[206],"LOCO":[207],"AD":[208],"dataset,":[209],"method":[211],"achieved":[212],"impressive":[213],"results":[214],"pixel-level":[217],"sPRO":[218],"82.9%":[220],"image-level":[223],"area":[224],"receiver":[227],"operating":[228],"characteristic":[229],"curve":[230],"(AUROC)":[231],"91.0%.":[233]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":1}],"updated_date":"2026-04-02T15:55:50.835912","created_date":"2025-10-10T00:00:00"}
